AyoubChLin / bert-base-uncased-zeroshot-nli

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Total runs: 74
24-hour runs: 17
7-day runs: 22
30-day runs: 54
Model's Last Updated: May 02 2026
zero-shot-classification

Introduction of bert-base-uncased-zeroshot-nli

Model Details of bert-base-uncased-zeroshot-nli

google-bert/bert-base-multilingual-cased — Zero-Shot NLI Fine-Tune

Model Description

Fine-tuned google-bert/bert-base-multilingual-cased for zero-shot text classification via NLI.

Quick Start
from transformers import pipeline
clf = pipeline("zero-shot-classification", model="<your-hf-repo>")
result = clf("Your text here", candidate_labels=["label_a", "label_b"])
print(result)
Training Data
Dataset Label column
AyoubChLin/CompanyDocuments document_type
AyoubChLin/ARxiv_Metadata_50k labels
AyoubChLin/CNN_News_Articles_2011-2022 label
Training Details
Parameter Value
Base model google-bert/bert-base-multilingual-cased
Epochs 8
Learning rate 2e-05
Effective batch 128
Scheduler cosine_with_restarts
Precision bf16
Flash Attention 2 True
Gradient Checkpointing False
LLRD True (factor=0.9)
Evaluation Results (Zero-Shot)
Dataset Acc@1 Macro-F1 MCC ROC-AUC Avg-Prec
CNN_News_Articles 0.9157 0.4866 0.8514 0.9489 0.6000
ARxiv_Metadata_top20 0.1733 0.2423 0.1808 0.8640 0.5206
Framework Versions
  • transformers: 4.56.0
  • torch: 2.8.0+cu129
  • datasets: 4.8.5'

Runs of AyoubChLin bert-base-uncased-zeroshot-nli on huggingface.co

74
Total runs
17
24-hour runs
26
3-day runs
22
7-day runs
54
30-day runs

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bert-base-uncased-zeroshot-nli is an open source model from GitHub that offers a free installation service, and any user can find bert-base-uncased-zeroshot-nli on GitHub to install. At the same time, huggingface.co provides the effect of bert-base-uncased-zeroshot-nli install, users can directly use bert-base-uncased-zeroshot-nli installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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Updated:January 25 2024